부산대학교 도서관

In South Korea, stationary frequency analysis methods are generally used for estimating design rainfalls in practice. However, due to climate change and/or variability, recent rainfall observations have significantly different patterns from the past so that the recent trends need to be considered to estimate extreme rainfall quantiles for hydrologic design. This study focused on estimating extreme rainfall quantiles in administrative districts across South Korea, after building nonstationary GEV model using annual maximum rainfall (AMR) datasets for 228 administrative districts from point rainfall measures from 1973 to 2012. A moving average method with 25-year window was used for investigating time-dependent statistics of AMR, such as mean, variance and skewness, and parameters of GEV distribution. From the analyses of relationships between statistics and distribution parameters, this study derived nonlinear regression equations for distribution parameters, which provide the estimates of distribution parameters at any future time. The overall results achieved in this study illustrate that the nonlinear regression equations can be easily incorporated into the hydrologic frequency analysis and provide appropriate estimates of design rainfalls in the near future.